A control problem for Burgers' equation with bounded input/output

A stabilization problem for Burgers' equation is considered. Using linearization, various controllers are constructed which minimize certain weighted energy functionals. These controllers produce the desired degree of stability for the closed-loop nonlinear system. A numerical scheme for computing the feedback gain functional is developed and several numerical experiments are performed to show the theoretical results

Effect of rotation rate on the forces of a rotating cylinder: Simulation and control

In this paper we present numerical solutions to several optimal control problems for an unsteady viscous flow. The main thrust of this work is devoted to simulation and control of an unsteady flow generated by a circular cylinder undergoing rotary motion. By treating the rotation rate as a control variable, we can formulate two optimal control problems and use a central difference/pseudospectral transform method to numerically compute the optimal control rates. Several types of rotations are considered as potential controls, and we show that a proper synchronization of forcing frequency with the natural vortex shedding frequency can greatly influence the flow. The results here indicate that using moving boundary controls for such systems may provide a feasible mechanism for flow control

Sensitivity calculations for a 2D, inviscid, supersonic forebody problem

The use of a sensitivity equation method to computer derivatives for optimization based design algorithms are discussed. The problem of designing an optimal forebody simulator is used to motivate the algorithm and to illustrate the basic ideas. Finally, how an existing computational fluid dynamics (CFD) code can be modified to compute sensitivities and a numerical example is presented

Parameter identification for an abstract Cauchy problem by quasilinearization

A parameter identification problem is considered in the context of a linear abstract Cauchy problem with a parameter-dependent evolution operator. Conditions are investigated under which the gradient of the state with respect to a parameter possesses smoothness properties which lead to local convergence of an estimation algorithm based on quasi-linearization. Numerical results are presented concerning estimation of unknown parameters in delay-differential equations

Feedback Control of Low Dimensional Models of Transition to Turbulence

The problem of controlling or delaying transition to turbulence in shear flows has been the subject of numerous papers over the past twenty years. This period has seen the development of several low dimensional models for parallel shear flows in an attempt to explain the failure of classical linear hydrodynamic stability theory to correctly predict transition. In recent years, ideas from robust control theory have been employed to attack this problem. In this paper we use these models to develop a scenario for transition that employs both classical bifurcation theory and robust control theory. In addition, we present numerical results to illustrate the ideas and to show how feedback can be used to delay transition. We close with a specific conjecture and discuss some previous results along this line

Transciptome Analysis Illuminates the Nature of the Intracellular Interaction in a Vertebrate-Algal Symbiosis

During embryonic development, cells of the green alga Oophila amblystomatis enter cells of the salamander Ambystoma maculatum forming an endosymbiosis. Here, using de novo dual-RNA seq, we compared the host salamander cells that harbored intracellular algae to those without algae and the algae inside the animal cells to those in the egg capsule. This two-by-two-way analysis revealed that intracellular algae exhibit hallmarks of cellular stress and undergo a striking metabolic shift from oxidative metabolism to fermentation. Culturing experiments with the alga showed that host glutamine may be utilized by the algal endosymbiont as a primary nitrogen source. Transcriptional changes in salamander cells suggest an innate immune response to the alga, with potential attenuation of NF-κB, and metabolic alterations indicative of modulation of insulin sensitivity. In stark contrast to its algal endosymbiont, the salamander cells did not exhibit major stress responses, suggesting that the host cell experience is neutral or beneficial

Hydrocarbon incorporation into the salt marsh ecosystem from the West Falmouth oil spill

Originally issued as Reference No. 71-69, series later renamed WHOI-.The oil barge "Florida" ran aground just off Little Island, West Falmouth, Massachusetts on September 16, 1969. About 175,000 gallons of Number Two fuel oil leaked into Buzzards Bay and the adjacent Wild Harbor Marsh. This report presents the results of analyses done on marsh muds and organisms collected nearly a year after the spill. We studied the incorporation of polluting hydrocarbons into, and their movement through the marsh ecosystem. Analyses of surface muds agreed well with observations on plant growth. The dead areas were the most heavily polluted. A deep mud core in the dead area showed oil has penetrated to at least 70 cm. Virtually all the marsh organisms living in the contaminated area were affected by the oil at least to the extent that they accumulated oil hydrocarbons in their tissues. Our data suggest that two processes may occur as the oil passes through the marsh ecosystem. There may be a progressive loss in the straight chain hydrocarbons in relation to branched chain, cyclic and aromatic hydrocarbons. There also appears to be a selection for the higher boiling fractions of the contaminants higher up the food chain.Supported by the Bureau of Commercial Fisheries, Fish and Wildlife Service Grant No. 14-17-0007- 1128 (G) and The National Science Foundation Grant No. GA 28365

Substructure in clusters containing wide-angle tailed radio galaxies. I. New redshifts

We present new redshifts and positions for 635 galaxies in nine rich clusters containing Wide-Angle Tailed (WAT) radio galaxies. Combined with existing data, we now have a sample of 18 WAT-containing clusters with more than 10 redshifts. This sample contains a substantial portion of the WAT clusters in the VLA 20 cm survey of Abell clusters, including 75% of WAT clusters in the complete survey (z0.09. It is a representative sample which should not contain biases other than selection by radio morphology. We graphically present the new data using histograms and sky maps. A semi-automated procedure is used to search for emission lines in the spectra in order to add and verify galaxy redshifts. We find that the average apparent fraction of emission line galaxies is about 9% in both the clusters and the field. We investigate the magnitude completeness of our redshift surveys with CCD data for a test case, Abell 690. This case indicates that our galaxy target lists are deeper than the detection limit of a typical MX exposure, and they are 82% complete down to R=19.0. The importance of the uniformity of the placement of fibers on targets is posited, and we evaluate this in our datasets. We find some cases of non-uniformities which may influence dynamical analyses. A second paper will use this database to look for correlations between the WAT radio morphology and the cluster's dynamical state.Comment: 15 pages, 5 figures, 7 tables. To appear in the Astronomical Journa

MouldingNet: Deep-Learning for 3D Object Reconstruction

With the rise of deep neural networks a number of approaches for learning over 3D data have gained popularity. In this paper, we take advantage of one of these approaches, bilateral convolutional layers to propose a novel end-to-end deep auto-encoder architecture to efficiently encode and reconstruct 3D point clouds. Bilateral convolutional layers project the input point cloud onto an even tessellation of a hyperplane in the $(d+1)$-dimensional space known as the permutohedral lattice and perform convolutions over this representation. In contrast to existing point cloud based learning approaches, this allows us to learn over the underlying geometry of the object to create a robust global descriptor. We demonstrate its accuracy by evaluating across the shapenet and modelnet datasets, in order to illustrate 2 main scenarios, known and unknown object reconstruction. These experiments show that our network generalises well from seen classes to unseen classes